Method to effectively predict tire saturation for evasive steering and active safety control

Abstract

A system operates a method for steering a vehicle. A sensor obtains a first stream of data related to road wheel angle for the vehicle and a second stream of data related to lateral acceleration for the vehicle. A processor determines a reduced tire model for the vehicle using the first stream of data and the second stream of data, obtains a measurement of a current road wheel angle and a measurement of a current lateral acceleration, determines a current slope from the current road wheel angle and the current lateral acceleration, compares the current slope to the reduced tire model to predict a level of saturation of a tire of the vehicle, and controls a steering actuator of the vehicle to steer the vehicle based on the level of saturation of the tire.

What is claimed is: 
     
         1 . A method of operating a vehicle, comprising:
 obtaining a first stream of data related to road wheel angle for the vehicle;   obtaining a second stream of data related to lateral acceleration for the vehicle;   determining a reduced tire model for the vehicle using the first stream of data and the second stream of data;   obtaining a measurement of a current road wheel angle and a measurement of a current lateral acceleration;   determining a current slope from the current road wheel angle and the current lateral acceleration;   comparing the current slope to the reduced tire model to predict a level of saturation of a tire of the vehicle; and   controlling a steering actuator of the vehicle to steer the vehicle based on the level of saturation of the tire.   
     
     
         2 . The method of  claim 1 , further comprising shifting the first stream of data in time to generate a third stream of data including time-shifted road wheel angle data, the third stream of data aligned with the second stream of data and determining the reduced tire model using the third stream of data and the second stream of data. 
     
     
         3 . The method of  claim 1 , wherein the reduced tire model includes a normal slope and a traction limit slope, further comprising comparing the current slope to the normal slope and the traction limit slope to predict the level of saturation. 
     
     
         4 . The method of  claim 1 , further comprising learning a yaw relation model for the vehicle and adjusting a model parameter of an adaptive vehicle model based on a comparison of a current yaw slope to a normal yaw slope of the yaw relation model and a yaw limit slope of the yaw relation model. 
     
     
         5 . The method of  claim 4 , wherein the model parameter includes at least one of: (i) a front axle tire capacity; and (ii) a rear axle tire capacity. 
     
     
         6 . The method of  claim 1 , further comprising sending a signal to a display when one of: (i) a predicted tire capacity is near a traction limit; and (ii) the predicted tire capacity is near the traction limit and a yaw rate has deviated from a desired yaw rate. 
     
     
         7 . The method of  claim 1 , further comprising adding a safety margin in excess of a maximum lateral deviation allowed by the reduced tire model to obtain a target trajectory for the vehicle when a lateral deviation of a reference trajectory exceeds the maximum lateral deviation. 
     
     
         8 . A system for operating a vehicle, comprising:
 a sensor for obtaining a first stream of data related to road wheel angle for the vehicle and a second stream of data related to lateral acceleration for the vehicle;   a processor configured to:
 determine a reduced tire model for the vehicle using the first stream of data and the second stream of data; 
 obtain a measurement of a current road wheel angle and a measurement of a current lateral acceleration; 
 determine a current slope from the current road wheel angle and the current lateral acceleration; 
 compare the current slope to the reduced tire model to predict a level of saturation of a tire of the vehicle; and 
 control a steering actuator of the vehicle to steer the vehicle based on the level of saturation of the tire. 
   
     
     
         9 . The system of  claim 8 , wherein the processor is further configured to shift the first stream of data in time to generate a third stream of data including time-shifted road wheel angle data, the third stream of data aligned with the second stream of data and determining the reduced tire model using the third stream of data and the second stream of data. 
     
     
         10 . The system of  claim 8 , wherein the reduced tire model includes a normal slope and a traction limit slope and the processor is further configured to compare the current slope to the normal slope and the traction limit slope to predict the level of saturation. 
     
     
         11 . The system of  claim 8 , wherein the processor is further configured to learn a yaw relation model for the vehicle and adjust a model parameter of an adaptive vehicle model based on a comparison of a current yaw slope to a normal yaw slope of the yaw relation model and a yaw limit slope of the yaw relation model. 
     
     
         12 . The system of  claim 11 , wherein the model parameter includes at least one of: (i) a front axle tire capacity; and (ii) a rear axle tire capacity. 
     
     
         13 . The system of  claim 8 , wherein the processor is further configured to send a signal to a display when one of: (i) a predicted tire capacity is near a traction limit; and (ii) the predicted tire capacity is near the traction limit and a yaw rate has deviated from a desired yaw rate. 
     
     
         14 . The system of  claim 8 , wherein the processor is further configured to add a safety margin in excess of a maximum lateral deviation allowed by the reduced tire model to obtain a target trajectory for the vehicle when a lateral deviation of a reference trajectory exceeds the maximum lateral deviation. 
     
     
         15 . A vehicle, comprising:
 a sensor for obtaining a first stream of data related to road wheel angle for the vehicle and a second stream of data related to lateral acceleration for the vehicle;   a steering actuator for steering the vehicle;   a processor configured to:
 determine a reduced tire model for the vehicle using the first stream of data and the second stream of data; 
 obtain a measurement of a current road wheel angle and a measurement of a current lateral acceleration; 
 determine a current slope from the current road wheel angle and the current lateral acceleration; 
 compare the current slope to the reduced tire model to predict a level of saturation of a tire of the vehicle; and 
 control the steering actuator to steer the vehicle based on the level of saturation of the tire. 
   
     
     
         16 . The vehicle of  claim 15 , wherein the processor is further configured to shift the first stream of data in time to generate a third stream of data including time-shifted road wheel angle data, the third stream of data aligned with the second stream of data and determining the reduced tire model using the third stream of data and the second stream of data. 
     
     
         17 . The vehicle of  claim 15 , wherein the reduced tire model includes a normal slope and a traction limit slope and the processor is further configured to compare the current slope to the normal slope and the traction limit slope to predict the level of saturation. 
     
     
         18 . The vehicle of  claim 15 , wherein the processor is further configured to learn a yaw relation model for the vehicle and adjust a model parameter of an adaptive vehicle model based on a comparison of a current yaw slope to a normal yaw slope of the yaw relation model and a yaw limit slope of the yaw relation model. 
     
     
         19 . The vehicle of  claim 15 , wherein the processor is further configured to send a signal to a display when one of: (i) a predicted tire capacity is near a traction limit; and (ii) the predicted tire capacity is near the traction limit and a yaw rate has deviated from a desired yaw rate. 
     
     
         20 . The vehicle of  claim 15 , wherein the processor is further configured to add a safety margin in excess of a maximum lateral deviation allowed by the reduced tire model to obtain a target trajectory for the vehicle when a lateral deviation of a reference trajectory exceeds the maximum lateral deviation.